Andrew Katumba

High Speed Direct Modulation of a Heterogeneously Integrated InP/SOI DFB Laser

An integrated laser source to a silicon photonics circuit is an important requirement for optical interconnects. We present direct modulation of a heterogeneously integrated distributed feedback laser on and coupled to a silicon waveguide. We demonstrate a 28 Gb/s pseudo-random bit sequence non-return-to-zero data transmission over 2 km non-zero dispersion shifted fiber with a 1-dB power penalty. Additionally, we show 40-Gb/s duobinary modulation generated using the bandwidth limitation of the laser for both back-to-back and fiber transmission configurations. Furthermore, we investigate the device performance for the pulse amplitude modulation (PAM-4) at 20 GBd for high-speed short-reach applications.

Low-Loss Photonic Reservoir Computing with Multimode Photonic Integrated Circuits

We present a numerical study of a passive integrated photonics reservoir computing platform based on multimodal Y-junctions. We propose a novel design of this junction where the level of adiabaticity is carefully tailored to capture the radiation loss in higher-order modes, while at the same time providing additional mode mixing that increases the richness of the reservoir dynamics. With this design, we report an overall average combination efficiency of 61% compared to the standard 50% for the single-mode case. We demonstrate that with this design, much more power is able to reach the distant nodes of the reservoir, leading to increased scaling prospects. We use the example of a header recognition task to confirm that such a reservoir can be used for bit-level processing tasks. The design itself is CMOS-compatible and can be fabricated through the known standard fabrication procedures.

A multiple-input strategy to efficient integrated photonic reservoir computing

Photonic reservoir computing has evolved into a viable contender for the next generation of analog computing platforms as industry looks beyond standard transistor-based computing architectures. Integrated photonic reservoir computing, particularly on the silicon-on-insulator platform, presents a CMOS-compatible, wide bandwidth, parallel platform for implementation of optical reservoirs. A number of demonstrations of the applicability of this platform for processing optical telecommunication signals have been made in the recent past. In this work, we take it a stage further by performing an architectural search for designs that yield the best performance while maintaining power efficiency. We present numerical simulations for an optical circuit model of a 16-node integrated photonic reservoir with the input signal injected in combinations of 2, 4, and 8 nodes, or into all 16 nodes. The reservoir is composed of a network of passive photonic integrated circuit components with the required nonlinearity introduced at the readout point with a photodetector. The resulting error performance on the temporal XOR task for these multiple input cases is compared with that of the typical case of input to a single node. We additionally introduce for the first time in our simulations a realistic model of a photodetector. Based on this, we carry out a full power-level exploration for each of the above input strategies. Multiple-input reservoirs achieve better performance and power efficiency than single-input reservoirs. For the same input power level, multiple-input reservoirs yield lower error rates. The best multiple-input reservoir designs can achieve the error rates of single-input ones with at least two orders of magnitude less total input power. These results can be generally attributed to the increase in richness of the reservoir dynamics and the fact that signals stay longer within the reservoir. If we account for all loss and noise contributions, the minimum input power for error-free performance for the optimal design is found to be in the ≈1 mW range.

All-optical NRZ wavelength conversion based on a single hybrid III-V/Si SOA and optical filtering.

We demonstrate all-optical wavelength conversion (AOWC) of non-return-to-zero (NRZ) signal based on cross-gain modulation in a single heterogeneously integrated III-V-on-silicon semiconductor optical amplifier (SOA) with an optical bandpass filter. The SOA is 500 μm long and consumes less than 250 mW electrical power. We experimentally demonstrate 12.5 Gb/s and 40 Gb/s AOWC for both wavelength up and down conversion.

Photonic reservoir computing approaches to nanoscale computation

This material is based on work in progress. Reservoir computing, originally a training technique for recurrent neural networks, exploits the computation that naturally occurs in physical dynamical systems. Reservoir computing with integrated nanophotonics potentially offers low-power, high-bandwidth signal processing for telecommunication applications. We present our recent results for optical signal regeneration. Our simulations show that a small-scale low-power integrated photonic reservoir achieves state-of-the-art performance for regenerating optical signals that have traversed fiber lengths of up to 200 km.

Silicon photonics for neuromorphic information processing

We present our latest results on silicon photonics neuromorphic information processing based a.o. on techniques like reservoir computing. We will discuss aspects like scalability, novel architectures for enhanced power efficiency, as well as all-optical readout. Additionally, we will touch upon new machine learning techniques to operate these integrated readouts. Finally, we will show how these systems can be used for high-speed low-power information processing for applications like recognition of biological cells.

Toward neuro-inspired computing using a small network of micro-ring resonators on an integrated photonic chip

We present in this work numerical simulations of the performance of an on-chip photonic reservoir computer using nonlinear microring resonator as neurons. We present dynamical properties of the nonlinear node and the reservoir computer, and we analyse the performance of the reservoir on a typical nonlinear Boolean task : the delayed XOR task. We study the performance for various designs (number of nodes, and length of the synapses in the reservoir), and with respect to the properties of the optical injection of the data (optical detuning and power). From this work, we find that such a reservoir has state-of-the art level of performance on this particular task - that is a bit error rate of 2.5 10-4 - at 20 Gb/s, with very good power efficiency (total injected power lower than 1.0 mW).

PAM-4 and Duobinary direct modulation of a hybrid InP/SOI DFB laser for 40 Gb/s transmission over 2 km single mode fiber

We demonstrate 40 Gb/s PAM-4 and Duobinary direct modulation of a heterogeneously integrated InP on SOI DFB laser. Transmission measurement was performed using a 2 km NZ-DSF with a PRBS 215 and 1.5 Vpp swing voltage.

An integrated Photonics Reservoir Computing approach to signal equalization for telecommunications

Photonic Reservoir Computing is a brain-inspired computing approach that brings the fast speeds and enormous bandwidth associated with lightwave technology together with the versatility of machine learning to enable the efficient computation of tasks requiring a finite amount of memory such as speech recognition, series prediction, header recognition etc. Broadly, our efforts focus on applying photonic reservoir computing implemented with the Silicon on Insulator (SOI) CMOS- compatible primitives to develop applications in the optical telecommunications space to take advantage of the aforementioned advantages. Specifically, this work presents our results on the implementation of a passive photonic reservoir chip that can be positioned at the receiver of a short or long metro link to invert impairments introduced to the optical transmitted signal due to a variety of imperfections and noise sources.